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Julia as a universal platform for statistical software development

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  • David Roodman

    (Open Philanthropy)

Abstract

The julia package integrates the Julia programming language into Stata. Users can transfer data between Stata and Julia, issue Julia commands to analyze and plot, and pass results back to Stata. Julia’s econometric ecosystem is not as mature as Stata’s, R’s, or Python’s. But Julia is an excellent envi- ronment for developing high-performance numerical applications, which can then be called from many platforms. For example, the boottest program for wild bootstrap–based inference (Roodman et al., 2019, Stata Journal 19: 4–60) and fwildclusterboot for R (Fischer and Roodman, 2021, “fwildclusterboot: Fast wild cluster bootstrap inference for linear regression models”) can both call the same Julia back end. And the program reghdfejl mimics reghdfe (Correia, 2016, https://scorreia.com/research/hdfe.pdf) in fitting linear models with high- dimensional fixed effects but calls a Julia package for tenfold acceleration on hard problems. reghdfejl also supports nonlinear fixed-effect models that cannot oth- erwise be fit in Stata—though preliminarily because the Julia package for that purpose is immature.

Suggested Citation

  • David Roodman, 2025. "Julia as a universal platform for statistical software development," Stata Journal, StataCorp LLC, vol. 25(2), pages 255-284, June.
    • Handle: RePEc:tsj:stataj:v:25:y:2025:i:2:p:255-284
    DOI: 10.1177/1536867X251341105
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